In many applications such as vehicle occupancy detection and vein pattern extraction, there is a need to capture a 2D view of the scene with multi (hyper) spectral bands. Conventionally, a preset number of filters mounted on a wheel using a servo-control action on a camera body are used. However, the approach has limited applications when the object of interest is in motion. The time delay between various captured events can be a problem for subsequent multi-spectral analysis.
Camera systems have arisen with a honeycombed lens structure positioned along the optical axis to capture a 2D scene. FIG. 1 shows an example scene captured on a 640×512 Xenics InGaAs IR Camera with a 4×4=16 filter grid. The wavelength of each filter is fixed in ranges from 1400 nm to 1800 nm. The last four images were outside the camera's detector range. The use of a filter grid of equal size for simultaneous multi-band capture results in reduced spatial resolution depending on the number of filters. Each image in FIG. 1 is only ¼ of the camera's spatial resolution in each direction. In applications where the spatial information and features are important, e.g. face detection, vein pattern detection, textual analysis, and the like, this assembly can be quite limiting. FIG. 2 shows 13 images captured at differing wavelength bands ranging from 1050 nm (upper-left) to 1650 nm (bottom-right) each at the camera's full resolution (256×320). The band in the middle seems brighter than others is due to the filter (1300 nm) which had higher transmission and wider bandwidth. To perform skin detection or other material detection such as fabric detection in a moving vehicle, it is desirable to capture images at a plurality of bands simultaneously. With such a multi-filter grid system, the spatial resolution of each band has to be reduced by a factor of 3 or 4 to fit 12 bands or 16 bands into the same capture. Face detection fails when the spatial resolution is reduced by more than ½ of the full camera resolution (i.e. <128×160). Hence, it is desirable to have a system that optimizes trade-offs between spatial and spectral resolution.